On the Question of Validity in Learning Analytics

Adam Cooper, May 15, 2015
Commentary by Stephen Downes

Good artcile outlining some core issues in learning analytics. For one thing, the author makes a useful distinction between 'reliable' and 'valid' analytics. "For learning analytics, it is entirely possible to have some kind of prediction that is highly statistically-significant and scores highly in all objective measures of performance but is still irrelevant to practice." Additionally, we have to ask questions about whether the results are generalizable, and whether the method was transparent. "Learning analytics undertaken without validity being accounted for would be ethically questionable, and I think we are not yet where we need to get to." Image: Nevit Dilmen.

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